To understand the dynamics of the innate immune signaling network in single cells is a fundamental goal of immunology. Using an approach that combines the latest technologies for live-cell imaging, high-throughput image analysis, microfluidic cell culture and computational network modeling, the Covert Lab studies how cells decode complex environmental information by measuring the single-cell responses of NFkB to combinations of stimuli and time-dependent stimuli (Nature, 2010; Science Signaling 2009). Although these and similar approaches have been extremely useful in characterizing phenotypic heterogeneity within a population of cells (also in studying p53, for example), the conclusions that can be drawn from them are limited by the relatively low number of measureable outputs as well as the fact that until now, virtually all of this kind of research has been performed in cultued cells. We propose to dramatically expand the scope of live-cell dynamic imaging of the immune system, developing new technologies to dramatically increase the number of measureable outputs, and enable in vivo measurements. Our Specific Aims are: (1) to create a library of constructs and cells that will enable monitoring of a variety of factors, encompassing multiple parallel signaling pathways and at endogenous expression levels, simultaneously in individual cells. (2) To understand how network dynamics control gene expression, we propose to develop methods to correlate the dynamics of transcription factors with the dynamics of endogenous gene expression in single cells, by integrating recently developed techniques for RNA FISH with our live cell imaging technology. This will be the first time that dynamic transcription factor activity has ever been directly compared with gene expression in individual cells. (3) The Covert Lab will partner with Tannishtha Reya at UCSD to integrate our methods for imaging and quantifying protein localization in single cells with her pioneering tools for monitoring cellular movement in vivo. By combining these approaches, we will be the first to observe the dynamics of transcription factors in individual cells as they move through the bone marrow of intact animals. In achieving these goals, we expect to achieve a significantly more detailed and system-level understanding of how environmental information is encoded in signaling network dynamics, and to have produced some first-of-its-kind technology for the scientific community.